Forecasting fuzzy time series on a heuristic high-order model

Chen first proposed the high-order fuzzy-time series model to overcome the drawback of existing fuzzy first-order forecasting models. His model involved easy calculations and forecasted more accurately than the other models. This study proposes an enhanced fuzzy-time series model, called heuristic high-order fuzzy time series model, to deal with forecasting problems. The proposed model aims to overcome the deficiency of Chen's model, which depends strongly on the highest-order fuzzy-time series to eliminate ambiguities at forecasting and requires a vast memory for data storage. The empirical analysis reveals that the proposed model yields more accurate forecasts.